To collect information about the genetic diversity of the plankton community and to study how plankton respond to environmental conditions, plankton samples were collected from five stations representing different trophic levels in a shallow, eutrophic lake (Lake Donghu), and investigated by PCR-DGGE fingerprinting. A total of 100 bands (61 of 16S rDNA bands and 39 of 18S rDNA bands) were detected. The DGGE bands unique to any single station accounted for 38% of the total bands, whereas common bands detected at all five stations accounted for only 11%. Using UPGMA clustering and MDS ordination of DGGE fingerprints, stations I and II were found to initially group together into one cluster, which was later joined by station V. Stations III and IV were isolated into two separate groups of one station each. Some differences in grouping relationships were found when analysis was completed on the basis of chemical characteristics and morphological composition, with zooplankton composition showing the greatest variability. However, the most similar stations (I and II) were always initially grouped into one cluster. Moreover, stations that exhibited the same or similar trophic level (stations III and IV), but different concentrations of heavy metals, were further differentiated by the DGGE method. Results of the present study indicated that PCR-DGGE fingerprinting was more sensitive than the traditional methods, as other studies suggested. Additionally, PCR-DGGE appears to be more appropriate for diversity characterization of the plankton community, as it is more canonical, systematic, and effective. Most importantly, fingerprinting results are more convenient for the comparative analyses between different studies. Therefore, the use of the described fingerprinting analysis may provide an operable and sensitive biomonitoring approach to identify critical, and potentially negative, stress within an aquatic ecosystem.

英文摘要:

To collect information about the genetic diversity of the plankton community and to study how plankton respond to environmental conditions, plankton samples were collected from five stations representing different trophic levels in a shallow, eutrophic lake (Lake Donghu), and investigated by PCR-DGGE fingerprinting. A total of 100 bands (61 of 16S rDNA bands and 39 of 18S rDNA bands) were detected. The DGGE bands unique to any single station accounted for 38% of the total bands, whereas common bands detected at all five stations accounted for only 11%. Using UPGMA clustering and MDS ordination of DGGE fingerprints, stations I and II were found to initially group together into one cluster, which was later joined by station V. Stations III and IV were isolated into two separate groups of one station each. Some differences in grouping relationships were found when analysis was completed on the basis of chemical characteristics and morphological composition, with zooplankton composition showing the greatest variability. However, the most similar stations (I and II) were always initially grouped into one cluster. Moreover, stations that exhibited the same or similar trophic level (stations III and IV), but different concentrations of heavy metals, were further differentiated by the DGGE method. Results of the present study indicated that PCR-DGGE fingerprinting was more sensitive than the traditional methods, as other studies suggested. Additionally, PCR-DGGE appears to be more appropriate for diversity characterization of the plankton community, as it is more canonical, systematic, and effective. Most importantly, fingerprinting results are more convenient for the comparative analyses between different studies. Therefore, the use of the described fingerprinting analysis may provide an operable and sensitive biomonitoring approach to identify critical, and potentially negative, stress within an aquatic ecosystem.